Insights on Transfer Optimization: Because Experience is the Best Teacher
By Abhishek Gupta, Yew-Soon Ong, Liang Feng. IEEE Transactions on Emerging Topics in Computational Intelligence, 2018
325 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/c7a109ea2c56a0b2dcfdb6dd85bfb40b67bbc0b6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Yaochu Jin
- Ponnuthurai Nagaratnam Suganthan
- Handing Wang
- Francisco Herrera
- Carlos Artemio Coello Coello
- Yew-Soon Ong
- Tinkle Chugh
- Swagatam Das
In Computational Theory and Mathematics
- Yaochu Jin
- Handing Wang
- Ponnuthurai Nagaratnam Suganthan
- Francisco Herrera
- Tinkle Chugh
- Carlos Artemio Coello Coello
- Kaisa Miettinen
- Yew-Soon Ong
Citations in the corpus
- Data-Driven Evolutionary Optimization: An Overview and Case Studies (2019, methodology): “Furthermore, transfer optimization techniques [115] including sequential transfer optimization,”
- A Tutorial On the design, experimentation and application of metaheuristic algorithms to real-World optimization problems (2021, methodology): “An example of this translations is the Random-Keys based encoding, often used in Transfer Optimization environments [67, 68].”
- Multifactorial Evolutionary Algorithm With Online Transfer Parameter Estimation: MFEA-II (2020, background): “The onset of knowledge transfer in multitasking occurs during subsequent sampling of candidate solutions from the mixture distribution specified in (1) [8], [44].”
- StarCraft Micromanagement With Reinforcement Learning and Curriculum Transfer Learning (2018, unknown): “The most widely used approach is transfer learning (TL) [50], [51].”